--------------------------------------------------------------------------------
      name:  <unnamed>
       log:  /Users/haselswerdtj/Library/CloudStorage/OneDrive-UniversityofMisso
> uri/Mizzou/Advising/Past students/Juhyun Bae/Gig Workers/Gig Workers JB & JH/D
> ata/gig_analysis.log
  log type:  text
 opened on:  25 Jun 2025, 10:22:59

. //program:  gig_analysis.do    
. //task: Analyses & figures for manuscript
. //project:   JB & JH Gig Workers
. //author: Juhyun Bae & Jake Haselswerdt  \ updated 2025-6-25
. 
. clear all

. set linesize 80

. macro drop _all

. set scheme s1mono

. set more off

. 
. use gig_wave1_weight.dta, clear 
(Forthright 2023 NEW data cleaned w. weight / JBJH 2-27-24)

. 
. //Setting up onewaygraph command 
. do onewaygraph.do

. //programs: for ttest graphs - onewaygraph - should run this first for figures
. //project:   JB & JH Gig Workers
. //author: Juhyun Bae & Jake Haselswerdt  \ updated 2025-6-10 [for increasing s
> ize in legend]
. 
. capture program drop onewaygraph

.         
. program define onewaygraph
  1.         syntax varlist(min=2 max=2 numeric) [if] [in] [aweight fweight pwei
> ght iweight] ///
>         [, BOnferroni SCheffe SIdak CI(string) BASEgroup(string) COlor(string)
>  NONote graph_option(string)]
  2.         
.         quiet {
  3.         set more off
  4.                 preserve
  5.                 marksample touse
  6.                 keep if `touse'
  7.                         
.                 if ("`weight'"! ="") loc wt [`weight' `exp']
  8.                         
.                 local x_var = word("`varlist'",-1)
  9.                 local y_var = word("`varlist'",1) 
 10.                 
.                 if ("`ci'"=="") loc ci = 95
 11.                 loc posttest = "bonferroni"
 12.                 if ("`scheffe'"!="") loc posttest = "scheffe"
 13.                 if ("`sidak'"!="") loc posttest = "sidak"
 14.                                 
.                 levelsof `x_var', local(levels)
 15.                 local ngroup = wordcount("`levels'")
 16.                 loc bn = 1
 17.                 if "`basegroup'"!=""{
 18.                         forv i = 1(1)`ngroup'{
 19.                                 if("`basegroup'" == word("`levels'",`i')) l
> oc bn = `i'
 20.                         }
 21.                         
.                         loc levels = subinstr("`levels'","`basegroup'","",.)
 22.                         loc levels = "`basegroup'" + " " + "`levels'"
 23.                         loc basegroup = "b`basegroup'"
 24.                 }
 25.                 
.                 local vallab: value label `x_var'
 26.                 if ("`color'"==""){
 27.                         loc col1 = "navy"
 28.                         loc col2 = "maroon"
 29.                         loc col3 = "orange"
 30.                         loc col4 = "forest_green"
 31.                         loc col5 = "purple"
 32.                         loc col6 = "black"
 33.                 }
 34.                 else {
 35.                         loc i = 1
 36.                         forv i = 1(1)`ngroup'{
 37.                                 loc col`i' = word("`color'",`i')
 38.                                 loc i = `i' + 1
 39.                         }
 40.                 }
 41. 
.                 loc i = 1
 42.                 foreach l of local levels{
 43.                         loc level`i' = "`l'"
 44.                         cap loc label`i' : label `vallab' `l'
 45.                         if ("`label`i''"=="") loc label`i' `l'
 46.                         loc i = `i' + 1
 47.                 }
 48.                 
.                 forv i = 1(1)`ngroup'{
 49.                         mean `y_var' `wt' if `x_var' == `level`i'', level(`
> ci')
 50.                         mat T = r(table)
 51.                         loc m`i' = T[1,1]
 52.                         loc l`i' = T[5,1]
 53.                         loc u`i' = T[6,1]
 54.                 }
 55.                 dis "Mean by groups"
 56.                 noi tab `x_var' `wt', sum(`y_var')
 57.                 dis "ANOVA results"
 58.                 noi oneway `y_var' `x_var' `wt', `bonferroni' `scheffe' `si
> dak'
 59.                 regress `y_var' i`basegroup'.`x_var' `wt'
 60.                 dis "Pairwise comparisons results"
 61.                 noi pwcompare `x_var', mcompare(`posttest') post pv
 62.                 matrix M = r(table_vs)
 63.                 if `bn' == 1 | "`basegroup'" == ""{
 64.                         forv i = 2(1)`ngroup'{
 65.                                 loc j = `i' - 1
 66.                                 loc pv`i' = M[4,`j']
 67.                         }
 68.                 }
 69.                 else if `bn' == 2 {
 70.                         loc pv2 = M[4,1]
 71.                         loc j = `ngroup'
 72.                         forv i = 3(1)`ngroup'{
 73.                                 loc pv`i' = M[4,`j']
 74.                                 loc j = `j' + 1
 75.                         }
 76.                 }
 77.                 else if `bn' == 3 {
 78.                         loc pv2 = M[4,2]
 79.                         loc pv3 = M[4,`ngroup']
 80.                         loc j = `ngroup' * 2 - 2
 81.                         forv i = 4(1)`ngroup'{
 82.                                 loc pv`i' = M[4,`j']
 83.                                 loc j = `j' + 1
 84.                         }
 85.                 }
 86.                 else if `bn' == 4 {
 87.                         loc pv2 = M[4,3]
 88.                         loc j = `ngroup' + 1
 89.                         loc pv3 = M[4,`j']
 90.                         loc j = `ngroup'* 2 - 2
 91.                         loc pv4 = M[4,`j']
 92.                         loc j = `ngroup'* 3 - 5
 93.                         forv i = 5(1)`ngroup'{
 94.                                 loc pv`i' = M[4,`j']
 95.                                 loc j = `j' + 1
 96.                         }
 97.                 }
 98.                 loc pv1 = 1
 99.                 
.                 clear
100.                 
.                 set obs `ngroup'
101.                 foreach x in n mean lower upper{
102.                         gen `x' = .
103.                 }
104.                 gen level = ""
105.                 gen label = ""
106.                                 
.                 forv i = 1(1)`ngroup'{
107.                         replace n = `i' in `i'
108.                         replace level = "`level`i''" in `i'
109.                         replace label = "`label`i''" in `i'
110.                         replace mean = `m`i'' in `i'
111.                         replace lower = `l`i'' in `i'
112.                         replace upper = `u`i'' in `i'
113.                 }
114.                 
.                 if strpos("`graph_option'","xtitle") == 0{
115.                         loc xtitle = `"xtitle("")"'
116.                 }
117.                 
.                 loc na = ""
118.                 loc sc = ""
119.                 loc r = ""
120.                 loc legend = ""
121.                 loc text = ""
122.                 if "`nonote'"==""{
123.                         loc note = `"note("Note: *p < 0.1, **p<0.05, ***p<0
> .01")"'
124.                 }
125.                 forv i = 1(1)`ngroup'{
126.                         if(`i' == 1) loc symbol "O"
127.                         if(`i' == 2) loc symbol "D"
128.                         if(`i' == 3) loc symbol "T"
129.                         if(`i' == 4) loc symbol "S"
130.                         if(`i' == 5) loc symbol "Oh"
131.                         if(`i' == 6) loc symbol "Dh"
132.                         if(`i' == 7) loc symbol "Th"
133.                         if(`i' == 8) loc symbol "Sh"
134.                         
.                         loc na = "`na'" + " (connect mean n if n == 0, ms(`sym
> bol') mc(`col`i'') lc(`col`i''))"
135.                         loc sc = "`sc'" + " (sc mean n if n == `i', ms(`sym
> bol') mc(`col`i''))"
136.                         loc r = "`r'" + " (rcap upper lower n if n == `i', 
> lc(`col`i''))"
137.                         loc legend = `"`legend' `i' "`label`i''""'
138.                         loc meantext: display %4.2f `m`i''
139.                         loc meantextstar = "`meantext'"
140.                         if (`pv`i'' <= 0.1) loc meantextstar = "`meantext'*
> "
141.                         if (`pv`i'' <= 0.05) loc meantextstar = "`meantext'
> **"
142.                         if (`pv`i'' <= 0.01) loc meantextstar = "`meantext'
> ***"
143.                         loc xpos = `i' + 0.1
144.                         loc text = `"`text' text(`meantext' `xpos' "`meante
> xtstar'", place(e) just(left) size(medium))"'
145.                 
.                 }
146.                 
.                 loc max = `ngroup' + 0.75
147.                 twoway `na'`sc'`r', `graph_option' legend(order(`legend') s
> ize(medium) col(3)) ///
>                 xlabel(none) xscale(ra(0.5 `max')) `xtitle' ///
>                 `text' `note'
148.                 restore
149.         }
150. end

. 
end of do-file

. 
. //Table 1 - descriptives by gig_mainsidenon
. 
. forvalues i = 1(1)3 {
  2.         asdoc sum partyID age gender income education white_nh black asian 
> multiracial hispanic if gig_mainsidenon == `i', save(Tables/summary.doc)
  3. }
(File Tables/summary.doc already exists, option append was assumed)

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
     partyID |        302    3.556291    1.837721          1          7
         age |        302    41.30464    11.96506         19         81
      gender |        302    1.569536    .5091839          1          3
      income |        299    3.397993    2.129718          1         11
   education |        302    4.089404    1.808604          1          9
-------------+---------------------------------------------------------
    white_nh |        302    .5562914    .4976458          0          1
       black |        302    .2251656    .4183846          0          1
       asian |        302    .0198675    .1397767          0          1
 multiracial |        302    .0662252     .249088          0          1
    hispanic |        302    .2019868    .4021487          0          1
Click to Open File:  Tables/summary.doc
(File Tables/summary.doc already exists, option append was assumed)

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
     partyID |        508    3.494094    1.897253          1          7
         age |        508    41.81693    11.95785         19         77
      gender |        508    1.503937    .5160006          1          3
      income |        501    4.013972    2.220316          1         11
   education |        508    4.271654    1.803192          1          9
-------------+---------------------------------------------------------
    white_nh |        508     .523622     .499934          0          1
       black |        508    .2165354    .4122893          0          1
       asian |        508    .0295276    .1694468          0          1
 multiracial |        508    .0944882     .292795          0          1
    hispanic |        508    .1850394    .3887123          0          1
Click to Open File:  Tables/summary.doc
(File Tables/summary.doc already exists, option append was assumed)

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
     partyID |        680    3.645588    1.852271          1          7
         age |        680    47.01176    13.35082         19         80
      gender |        680    1.580882    .5255637          1          3
      income |        668    3.606287    2.002043          1         11
   education |        680    4.042647    1.799101          1          9
-------------+---------------------------------------------------------
    white_nh |        680    .6617647    .4734573          0          1
       black |        680    .1308824    .3375199          0          1
       asian |        680        .025    .1562399          0          1
 multiracial |        680    .0647059    .2461872          0          1
    hispanic |        680    .1382353    .3454008          0          1
Click to Open File:  Tables/summary.doc

. 
. * with weight // the result has no difference with without weighting.
. forvalues i = 1(1)3 {
  2.         asdoc sum partyID age gender income education white_nh black asian 
> multiracial hispanic if gig_mainsidenon == `i' [aw=ww], save(Tables/summary_ww
> .doc)
  3. }
(File Tables/summary_ww.doc already exists, option append was assumed)

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
     partyID |        302    3.556291    1.837721          1          7
         age |        302    41.30464    11.96506         19         81
      gender |        302    1.569536    .5091839          1          3
      income |        299    3.397993    2.129718          1         11
   education |        302    4.089404    1.808604          1          9
-------------+---------------------------------------------------------
    white_nh |        302    .5562914    .4976458          0          1
       black |        302    .2251656    .4183846          0          1
       asian |        302    .0198675    .1397767          0          1
 multiracial |        302    .0662252     .249088          0          1
    hispanic |        302    .2019868    .4021487          0          1
Click to Open File:  Tables/summary_ww.doc
(File Tables/summary_ww.doc already exists, option append was assumed)

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
     partyID |        508    3.494094    1.897253          1          7
         age |        508    41.81693    11.95785         19         77
      gender |        508    1.503937    .5160006          1          3
      income |        501    4.013972    2.220316          1         11
   education |        508    4.271654    1.803192          1          9
-------------+---------------------------------------------------------
    white_nh |        508     .523622     .499934          0          1
       black |        508    .2165354    .4122893          0          1
       asian |        508    .0295276    .1694468          0          1
 multiracial |        508    .0944882     .292795          0          1
    hispanic |        508    .1850394    .3887123          0          1
Click to Open File:  Tables/summary_ww.doc
(File Tables/summary_ww.doc already exists, option append was assumed)

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
     partyID |        680    3.645588    1.852271          1          7
         age |        680    47.01176    13.35082         19         80
      gender |        680    1.580882    .5255637          1          3
      income |        668    3.606287    2.002043          1         11
   education |        680    4.042647    1.799101          1          9
-------------+---------------------------------------------------------
    white_nh |        680    .6617647    .4734573          0          1
       black |        680    .1308824    .3375199          0          1
       asian |        680        .025    .1562399          0          1
 multiracial |        680    .0647059    .2461872          0          1
    hispanic |        680    .1382353    .3454008          0          1
Click to Open File:  Tables/summary_ww.doc

.   
. 
. //Figure 1 - coverage by employer-provided benefits /// JB updated for having 
> grid (2025-6-10)
. foreach w in nw ww{
  2.         foreach p in healthins_1 workerscomp_01 retire_01 FMLA_01 famleave_
> 01{
  3.                 local label: variable label `p'
  4.                 local title=subinstr("`label'", "Covered by ", "", .)
  5.                 local title=subinstr("`title'", "insurance", "", .)
  6.                 local Title = upper(substr(`"`title'"'), 1, 1) + substr(`"`
> title'"', 2, .)
  7.                 onewaygraph `p' gig_mainsidenon [aw=`w'], bo graph_option(s
> cheme(s1color) ylabel(0(0.2)0.8, grid) xtitle(`Title', size(large)) aspect(1))
>  nonote 
  8.                 graph save "Figures/`p'_`w'.gph", replace
  9.         } 
 10.         grc1leg "Figures/healthins_1_`w'.gph" "Figures/workerscomp_01_`w'.g
> ph" "Figures/retire_01_`w'.gph", row(1) saving("Figures/insleave1_`w'.gph", re
> place)
 11.         grc1leg "Figures/FMLA_01_`w'.gph" "Figures/famleave_01_`w'.gph" , r
> ow(1) saving("Figures/insleave2_`w'.gph", replace)
 12.         local note = cond("`w'"=="ww", " Sampling weights used.", "")
 13.         grc1leg "Figures/insleave1_`w'.gph" "Figures/insleave2_`w'.gph", co
> l(1) note("Note: *p < 0.1, **p<0.05, ***p<0.01 `note'") 
 14. gr export "Figures/insleave_`w'.png", as(png) replace
 15. }

   Gig work |
main/side/n | Summary of Covered by employer-provided health
         on |                    insurance
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |           0           0         302         302
  Gig: side |           0           0         508         508
  Non-gig w |           0           0         680         680
------------+------------------------------------------------
      Total |           0           0       1,490       1,490

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      11.7726167      2   5.88630835     27.49     0.0000
 Within groups      318.444833   1487   .214152544
------------------------------------------------------------------------
    Total            330.21745   1489   .221771289

Bartlett's equal-variances test: chi2(2) =  35.6108    Prob>chi2 = 0.000

         Comparison of Covered by employer-provided health insurance
                    by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |          0
         |      0.000
         |
Non-gig  |          0         -0
         |      0.000      1.000

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |   .2282291   .0336255     6.79   0.000
Non-gig worker vs Gig: main job  |   .2149591   .0320007     6.72   0.000
Non-gig worker vs Gig: side job  |    -.01327   .0271384    -0.49   1.000
-------------------------------------------------------------------------
file Figures/healthins_1_nw.gph saved

   Gig work |
main/side/n |   Summary of Covered by workers' compensation
         on |                    insurance
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |   .32119205   .46770938         302         302
  Gig: side |   .51976285    .5001037         506         506
  Non-gig w |    .4904271   .50027688         679         679
------------+------------------------------------------------
      Total |     .466039   .49901314       1,487       1,487

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      8.20045119      2    4.1002256     16.82     0.0000
 Within groups      361.834519   1484     .2438238
------------------------------------------------------------------------
    Total            370.03497   1486   .249014112

Bartlett's equal-variances test: chi2(2) =   2.1054    Prob>chi2 = 0.349

           Comparison of Covered by workers' compensation insurance
                    by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |    .198571
         |      0.000
         |
Non-gig  |    .169235   -.029336
         |      0.000      0.936

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |   .1985708   .0359058     5.53   0.000
Non-gig worker vs Gig: main job  |    .169235   .0341534     4.96   0.000
Non-gig worker vs Gig: side job  |  -.0293357   .0289993    -1.01   0.936
-------------------------------------------------------------------------
file Figures/workerscomp_01_nw.gph saved

   Gig work |
main/side/n |   Summary of Covered by retirement or pension
         on |                      plan
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |   .37541528   .48503633         301         301
  Gig: side |   .59207921   .49193559         505         505
  Non-gig w |   .47787611   .49987907         678         678
------------+------------------------------------------------
      Total |   .49595687    .5001522       1,484       1,484

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      9.26120973      2   4.63060486     18.96     0.0000
 Within groups      361.714532   1481   .244236686
------------------------------------------------------------------------
    Total           370.975741   1483   .250152219

Bartlett's equal-variances test: chi2(2) =   0.4065    Prob>chi2 = 0.816

             Comparison of Covered by retirement or pension plan
                    by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |    .216664
         |      0.000
         |
Non-gig  |    .102461   -.114203
         |      0.008      0.000

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |   .2166639   .0359869     6.02   0.000
Non-gig worker vs Gig: main job  |   .1024608   .0342294     2.99   0.008
Non-gig worker vs Gig: side job  |  -.1142031   .0290494    -3.93   0.000
-------------------------------------------------------------------------
file Figures/retire_01_nw.gph saved

   Gig work |
main/side/n |
         on |           Summary of Covered by FMLA
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |   .26821192   .44376386         302         302
  Gig: side |   .46442688    .4992265         506         506
  Non-gig w |   .38404727   .48672877         677         677
------------+------------------------------------------------
      Total |   .38787879   .48743084       1,485       1,485

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      7.29958946      2   3.64979473     15.67     0.0000
 Within groups      345.282229   1482    .23298396
------------------------------------------------------------------------
    Total           352.581818   1484   .237588826

Bartlett's equal-variances test: chi2(2) =   5.2884    Prob>chi2 = 0.071

     Comparison of Covered by FMLA by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |    .196215
         |      0.000
         |
Non-gig  |    .115835    -.08038
         |      0.002      0.014

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |    .196215   .0350986     5.59   0.000
Non-gig worker vs Gig: main job  |   .1158353   .0334008     3.47   0.002
Non-gig worker vs Gig: side job  |  -.0803796   .0283652    -2.83   0.014
-------------------------------------------------------------------------
file Figures/FMLA_01_nw.gph saved

   Gig work |
main/side/n |     Summary of Covered by paid family leave
         on |                    benefits
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |   .27574751   .44763436         301         301
  Gig: side |   .44664032   .49763657         506         506
  Non-gig w |   .32842415   .46998621         679         679
------------+------------------------------------------------
      Total |   .35800808   .47957592       1,486       1,486

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      6.60604471      2   3.30302236     14.62     0.0000
 Within groups      334.933659   1483   .225848725
------------------------------------------------------------------------
    Total           341.539704   1485   .229993067

Bartlett's equal-variances test: chi2(2) =   4.4364    Prob>chi2 = 0.109

             Comparison of Covered by paid family leave benefits
                    by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |    .170893
         |      0.000
         |
Non-gig  |    .052677   -.118216
         |      0.329      0.000

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |   .1708928   .0345929     4.94   0.000
Non-gig worker vs Gig: main job  |   .0526766   .0329082     1.60   0.329
Non-gig worker vs Gig: side job  |  -.1182162   .0279099    -4.24   0.000
-------------------------------------------------------------------------
file Figures/famleave_01_nw.gph saved
file Figures/insleave1_nw.gph saved
file Figures/insleave2_nw.gph saved
file
    /Users/haselswerdtj/Library/CloudStorage/OneDrive-UniversityofMissouri/Miz
    > zou/Advising/Past students/Juhyun Bae/Gig Workers/Gig Workers JB &
    JH/Data/Figures/insleave_nw.png saved as PNG format

   Gig work |
main/side/n | Summary of Covered by employer-provided health
         on |                    insurance
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |           0           0         286         302
  Gig: side |           0           0         466         508
  Non-gig w |           0           0         676         680
------------+------------------------------------------------
      Total |           0           0       1,427       1,490

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      8.37772131      2   4.18886066     20.06     0.0000
 Within groups       310.45331   1487   .208778285
------------------------------------------------------------------------
    Total           318.831031   1489   .214124265

Bartlett's equal-variances test: chi2(2) =  31.6695    Prob>chi2 = 0.000

         Comparison of Covered by employer-provided health insurance
                    by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |          0
         |      0.000
         |
Non-gig  |          0         -0
         |      0.000      1.000

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |   .1884305   .0336065     5.61   0.000
Non-gig worker vs Gig: main job  |   .1866558   .0315559     5.92   0.000
Non-gig worker vs Gig: side job  |  -.0017748    .026933    -0.07   1.000
-------------------------------------------------------------------------
file Figures/healthins_1_ww.gph saved

   Gig work |
main/side/n |   Summary of Covered by workers' compensation
         on |                    insurance
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |   .34620493   .47654912         286         302
  Gig: side |   .48868647   .50036667         464         506
  Non-gig w |   .50818189    .5003016         675         679
------------+------------------------------------------------
      Total |   .46933915   .49922692       1,424       1,487

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      5.76693207      2   2.88346603     11.74     0.0000
 Within groups      364.585157   1484    .24567733
------------------------------------------------------------------------
    Total           370.352089   1486   .249227516

Bartlett's equal-variances test: chi2(2) =   2.4219    Prob>chi2 = 0.298

           Comparison of Covered by workers' compensation insurance
                    by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |    .142482
         |      0.000
         |
Non-gig  |    .161977    .019495
         |      0.000      1.000

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |   .1424815   .0364814     3.91   0.000
Non-gig worker vs Gig: main job  |    .161977   .0342396     4.73   0.000
Non-gig worker vs Gig: side job  |   .0194954   .0292587     0.67   1.000
-------------------------------------------------------------------------
file Figures/workerscomp_01_ww.gph saved

   Gig work |
main/side/n |   Summary of Covered by retirement or pension
         on |                      plan
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |   .42938837   .49581318         285         301
  Gig: side |   .58069531   .49393459         463         505
  Non-gig w |    .4625634   .49896464         670         678
------------+------------------------------------------------
      Total |   .49444466   .50013768       1,419       1,484

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      5.57859782      2   2.78929891     11.31     0.0000
 Within groups      365.375603   1481   .246708713
------------------------------------------------------------------------
    Total           370.954201   1483   .250137695

Bartlett's equal-variances test: chi2(2) =   1.3475    Prob>chi2 = 0.510

             Comparison of Covered by retirement or pension plan
                    by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |    .151307
         |      0.000
         |
Non-gig  |    .033175   -.118132
         |      1.000      0.000

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |   .1513069   .0365533     4.14   0.000
Non-gig worker vs Gig: main job  |    .033175   .0343297     0.97   1.000
Non-gig worker vs Gig: side job  |  -.1181319   .0293463    -4.03   0.000
-------------------------------------------------------------------------
file Figures/retire_01_ww.gph saved

   Gig work |
main/side/n |
         on |           Summary of Covered by FMLA
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |   .29359083   .45616255         286         302
  Gig: side |   .42702824   .49513597         465         506
  Non-gig w |   .37152684   .48357011         674         677
------------+------------------------------------------------
      Total |   .37400422   .48402772       1,424       1,485

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      3.29336427      2   1.64668214      7.09     0.0009
 Within groups      344.382356   1482   .232376758
------------------------------------------------------------------------
    Total            347.67572   1484    .23428283

Bartlett's equal-variances test: chi2(2) =   2.8849    Prob>chi2 = 0.236

     Comparison of Covered by FMLA by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |    .133437
         |      0.000
         |
Non-gig  |    .077936   -.055501
         |      0.059      0.151

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |   .1334374    .035489     3.76   0.001
Non-gig worker vs Gig: main job  |    .077936   .0333286     2.34   0.058
Non-gig worker vs Gig: side job  |  -.0555014   .0284658    -1.95   0.154
-------------------------------------------------------------------------
file Figures/FMLA_01_ww.gph saved

   Gig work |
main/side/n |     Summary of Covered by paid family leave
         on |                    benefits
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |   .31192961   .46405275         283         301
  Gig: side |   .44625655   .49759519         465         506
  Non-gig w |   .31603283   .46526863         675         679
------------+------------------------------------------------
      Total |   .35775118   .47949974       1,423       1,486

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      5.64978053      2   2.82489026     12.48     0.0000
 Within groups      335.781414   1483   .226420374
------------------------------------------------------------------------
    Total           341.431195   1485   .229919997

Bartlett's equal-variances test: chi2(2) =   1.2756    Prob>chi2 = 0.528

             Comparison of Covered by paid family leave benefits
                    by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |    .134327
         |      0.000
         |
Non-gig  |    .004103   -.130224
         |      1.000      0.000

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |   .1343269   .0350997     3.83   0.000
Non-gig worker vs Gig: main job  |   .0041032   .0329657     0.12   1.000
Non-gig worker vs Gig: side job  |  -.1302237   .0280664    -4.64   0.000
-------------------------------------------------------------------------
file Figures/famleave_01_ww.gph saved
file Figures/insleave1_ww.gph saved
file Figures/insleave2_ww.gph saved
file
    /Users/haselswerdtj/Library/CloudStorage/OneDrive-UniversityofMissouri/Miz
    > zou/Advising/Past students/Juhyun Bae/Gig Workers/Gig Workers JB &
    JH/Data/Figures/insleave_ww.png saved as PNG format

. 
. //Figure 2 - coverage by means-tested social assistance
. foreach w in nw ww{
  2.         foreach p in welfareben_3 welfareben_4 welfareben_2 healthins_4{
  3.                 local label: variable label `p'
  4.                 local title=subinstr("`label'", "Benefited: ", "", .)
  5.                 local title=subinstr("`title'", "Covered by insurance from"
> , "ACA", .)
  6.                 local Title = upper(substr(`"`title'"'), 1, 1) + substr(`"`
> title'"', 2, .)
  7.                 onewaygraph `p' gig_mainsidenon [aw=`w'], bo graph_option(s
> cheme(s1color) ylabel(0(0.2)0.8, grid) xtitle(`Title', size(large)) /*aspect(1
> )*/) nonote 
  8.                 graph save "Figures/`p'_`w'.gph", replace
  9.         } 
 10.         local note = cond("`w'"=="ww", " Sampling weights used.", "")
 11.         grc1leg "Figures/welfareben_3_`w'.gph" "Figures/welfareben_4_`w'.gp
> h" "Figures/welfareben_2_`w'.gph" "Figures/healthins_4_`w'.gph", note("Note: *
> p < 0.1, **p<0.05, ***p<0.01 `note'") 
 12.         gr export "Figures/meanstested_`w'.png", as(png) replace
 13. }

   Gig work |
main/side/n |
         on |           Summary of Benefited: TANF
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |         .21   .40798879         300         300
  Gig: side |   .13663366   .34380076         505         505
  Non-gig w |   .07680945   .26648575         677         677
------------+------------------------------------------------
      Total |   .12415655   .32987137       1,482       1,482

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      3.80701003      2   1.90350502     17.89     0.0000
 Within groups      157.348186   1479   .106388226
------------------------------------------------------------------------
    Total           161.155196   1481   .108815122

Bartlett's equal-variances test: chi2(2) =  86.2574    Prob>chi2 = 0.000

     Comparison of Benefited: TANF by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |   -.073366
         |      0.006
         |
Non-gig  |   -.133191   -.059824
         |      0.000      0.006

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |  -.0733663    .023776    -3.09   0.006
Non-gig worker vs Gig: main job  |  -.1331905   .0226224    -5.89   0.000
Non-gig worker vs Gig: side job  |  -.0598242   .0191785    -3.12   0.006
-------------------------------------------------------------------------
file Figures/welfareben_3_nw.gph saved

   Gig work |
main/side/n |
         on |           Summary of Benefited: SNAP
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |   .56856187   .49610727         299         299
  Gig: side |   .43253968   .49592043         504         504
  Non-gig w |   .38724036   .48748112         674         674
------------+------------------------------------------------
      Total |    .4394042   .49648267       1,477       1,477

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      6.84557782      2   3.42278891     14.13     0.0000
 Within groups      356.981098   1474   .242185277
------------------------------------------------------------------------
    Total           363.826676   1476   .246495038

Bartlett's equal-variances test: chi2(2) =   0.2186    Prob>chi2 = 0.896

     Comparison of Benefited: SNAP by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |   -.136022
         |      0.000
         |
Non-gig  |   -.181322   -.045299
         |      0.000      0.355

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |  -.1360222   .0359237    -3.79   0.000
Non-gig worker vs Gig: main job  |  -.1813215   .0341952    -5.30   0.000
Non-gig worker vs Gig: side job  |  -.0452993   .0289802    -1.56   0.355
-------------------------------------------------------------------------
file Figures/welfareben_4_nw.gph saved

   Gig work |
main/side/n |
         on |         Summary of Benefited: Medicaid
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |   .55666667   .49760855         300         300
  Gig: side |   .42178218   .49433376         505         505
  Non-gig w |   .37721893   .48504932         676         676
------------+------------------------------------------------
      Total |   .42876435   .49506663       1,481       1,481

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      6.72840445      2   3.36420223     13.97     0.0000
 Within groups      356.006234   1478   .240870253
------------------------------------------------------------------------
    Total           362.734639   1480   .245090972

Bartlett's equal-variances test: chi2(2) =   0.3524    Prob>chi2 = 0.838

   Comparison of Benefited: Medicaid by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |   -.134884
         |      0.001
         |
Non-gig  |   -.179448   -.044563
         |      0.000      0.369

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |  -.1348845   .0357753    -3.77   0.001
Non-gig worker vs Gig: main job  |  -.1794477   .0340473    -5.27   0.000
Non-gig worker vs Gig: side job  |  -.0445632   .0288667    -1.54   0.369
-------------------------------------------------------------------------
file Figures/welfareben_2_nw.gph saved

   Gig work |
main/side/n |
         on |  Summary of Covered by insurance from exchange
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |           0           0         302         302
  Gig: side |           0           0         508         508
  Non-gig w |           0           0         680         680
------------+------------------------------------------------
      Total |           0           0       1,490       1,490

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      1.28252445      2   .641262223      5.85     0.0029
 Within groups       162.99667   1487   .109614439
------------------------------------------------------------------------
    Total           164.279195   1489   .110328539

Bartlett's equal-variances test: chi2(2) =  29.2579    Prob>chi2 = 0.000

               Comparison of Covered by insurance from exchange
                    by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |          0
         |      0.464
         |
Non-gig  |         -0         -0
         |      0.484      0.002

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |   .0342468    .024057     1.42   0.464
Non-gig worker vs Gig: main job  |  -.0320802   .0228945    -1.40   0.484
Non-gig worker vs Gig: side job  |   -.066327   .0194158    -3.42   0.002
-------------------------------------------------------------------------
file Figures/healthins_4_nw.gph saved
file
    /Users/haselswerdtj/Library/CloudStorage/OneDrive-UniversityofMissouri/Miz
    > zou/Advising/Past students/Juhyun Bae/Gig Workers/Gig Workers JB &
    JH/Data/Figures/meanstested_nw.png saved as PNG format

   Gig work |
main/side/n |
         on |           Summary of Benefited: TANF
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |   .21899593   .41425686         283         300
  Gig: side |   .14192881   .34932315         463         505
  Non-gig w |   .06803305   .25198878         672         677
------------+------------------------------------------------
      Total |   .12229932   .32774178       1,419       1,482

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      5.01947664      2   2.50973832     24.09     0.0000
 Within groups      154.061655   1479   .104166095
------------------------------------------------------------------------
    Total           159.081132   1481   .107414674

Bartlett's equal-variances test: chi2(2) = 106.3719    Prob>chi2 = 0.000

     Comparison of Benefited: TANF by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |   -.077067
         |      0.003
         |
Non-gig  |   -.150963   -.073896
         |      0.000      0.000

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |  -.0770671   .0238195    -3.24   0.004
Non-gig worker vs Gig: main job  |  -.1509629   .0223735    -6.75   0.000
Non-gig worker vs Gig: side job  |  -.0738958   .0190662    -3.88   0.000
-------------------------------------------------------------------------
file Figures/welfareben_3_ww.gph saved

   Gig work |
main/side/n |
         on |           Summary of Benefited: SNAP
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |   .54058886   .49918528         282         299
  Gig: side |   .40292435   .49097312         462         504
  Non-gig w |   .34753145   .47653989         666         674
------------+------------------------------------------------
      Total |    .4042994   .49092216       1,409       1,477

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      7.73547107      2   3.86773554     16.38     0.0000
 Within groups       347.98727   1474    .23608363
------------------------------------------------------------------------
    Total           355.722741   1476   .241004567

Bartlett's equal-variances test: chi2(2) =   0.3655    Prob>chi2 = 0.833

     Comparison of Benefited: SNAP by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |   -.137665
         |      0.000
         |
Non-gig  |   -.193057   -.055393
         |      0.000      0.159

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |  -.1376645   .0358726    -3.84   0.000
Non-gig worker vs Gig: main job  |  -.1930574   .0337298    -5.72   0.000
Non-gig worker vs Gig: side job  |  -.0553929   .0287423    -1.93   0.162
-------------------------------------------------------------------------
file Figures/welfareben_4_ww.gph saved

   Gig work |
main/side/n |
         on |         Summary of Benefited: Medicaid
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |   .54052843   .49918741         283         300
  Gig: side |   .42342396   .49459125         463         505
  Non-gig w |    .3635811   .48138621         671         676
------------+------------------------------------------------
      Total |   .41847668   .49347581       1,418       1,481

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups       6.5307521      2   3.26537605     13.64     0.0000
 Within groups      353.876446   1478   .239429259
------------------------------------------------------------------------
    Total           360.407198   1480   .243518377

Bartlett's equal-variances test: chi2(2) =   0.2144    Prob>chi2 = 0.898

   Comparison of Benefited: Medicaid by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |   -.117104
         |      0.003
         |
Non-gig  |   -.176947   -.059843
         |      0.000      0.113

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |  -.1171045   .0361135    -3.24   0.004
Non-gig worker vs Gig: main job  |  -.1769473   .0339263    -5.22   0.000
Non-gig worker vs Gig: side job  |  -.0598429   .0289154    -2.07   0.116
-------------------------------------------------------------------------
file Figures/welfareben_2_ww.gph saved

   Gig work |
main/side/n |
         on |  Summary of Covered by insurance from exchange
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |           0           0         286         302
  Gig: side |           0           0         466         508
  Non-gig w |           0           0         676         680
------------+------------------------------------------------
      Total |           0           0       1,427       1,490

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      .684475919      2   .342237959      3.16     0.0427
 Within groups      161.051213   1487   .108306128
------------------------------------------------------------------------
    Total           161.735689   1489   .108620342

Bartlett's equal-variances test: chi2(2) =   9.2636    Prob>chi2 = 0.010

               Comparison of Covered by insurance from exchange
                    by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |          0
         |      1.000
         |
Non-gig  |         -0         -0
         |      0.763      0.037

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |   .0224802   .0242051     0.93   1.000
Non-gig worker vs Gig: main job  |  -.0259584   .0227282    -1.14   0.761
Non-gig worker vs Gig: side job  |  -.0484387   .0193985    -2.50   0.038
-------------------------------------------------------------------------
file Figures/healthins_4_ww.gph saved
file
    /Users/haselswerdtj/Library/CloudStorage/OneDrive-UniversityofMissouri/Miz
    > zou/Advising/Past students/Juhyun Bae/Gig Workers/Gig Workers JB &
    JH/Data/Figures/meanstested_ww.png saved as PNG format

. 
. //Figure B1 (formerly 3) - overcoming an economic crisis - NOTE: This was reve
> rse coded before so the findings for crisisgov are actually the opposite of wh
> at we thought! Have to figure out what to do. I expect this is because gig wor
> kers are more experienced with means tested "unsubmerged" welfare programs.
. foreach w in nw ww{
  2.         foreach c in crisis crisisgov{
  3.                 local Title: variable label `c'
  4.                 onewaygraph `c' gig_mainsidenon [aw=`w'], bo graph_option(s
> cheme(s1color) ylabel(1(0.5)4, grid) xtitle(`Title', size(large))) nonote 
  5.                 graph save "Figures/`c'_`w'.gph", replace
  6.         }
  7.         local note = cond("`w'"=="ww", " Sampling weights used.", "")
  8.         grc1leg "Figures/crisis_`w'.gph" "Figures/crisisgov_`w'.gph", schem
> e(s1color) note("Note: *p < 0.1, **p<0.05, ***p<0.01 `note'") 
  9.                 gr export "Figures/crisismerge_`w'.png", as(png) replace //
>  JB: 04-03: add the combined one
 10. }

   Gig work |
main/side/n |
         on |       Summary of Likelihood of overcoming
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |           3           1         302         302
  Gig: side |           3           1         508         508
  Non-gig w |           3           1         679         679
------------+------------------------------------------------
      Total |           3           1       1,489       1,489

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups       3.8628999      2   1.93144995      2.51     0.0812
 Within groups      1141.34194   1486   .768063214
------------------------------------------------------------------------
    Total           1145.20484   1488   .769626906

Bartlett's equal-variances test: chi2(2) =   0.8819    Prob>chi2 = 0.643

 Comparison of Likelihood of overcoming by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |          0
         |      0.626
         |
Non-gig  |         -0         -0
         |      1.000      0.078

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |    .080122   .0636804     1.26   0.626
Non-gig worker vs Gig: main job  |  -.0344049    .060617    -0.57   1.000
Non-gig worker vs Gig: side job  |  -.1145269   .0514111    -2.23   0.078
-------------------------------------------------------------------------
file Figures/crisis_nw.gph saved

   Gig work |
main/side/n |
         on |  Summary of Helpfulness of government programs
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |           3           1         301         301
  Gig: side |           3           1         508         508
  Non-gig w |           3           1         679         679
------------+------------------------------------------------
      Total |           3           1       1,488       1,488

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      25.4309956      2   12.7154978     16.28     0.0000
 Within groups      1159.59857   1485   .780874461
------------------------------------------------------------------------
    Total           1185.02957   1487   .796926409

Bartlett's equal-variances test: chi2(2) =   1.6456    Prob>chi2 = 0.439

               Comparison of Helpfulness of government programs
                    by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |         -0
         |      0.010
         |
Non-gig  |         -0         -0
         |      0.000      0.009

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |  -.1892118   .0642761    -2.94   0.010
Non-gig worker vs Gig: main job  |  -.3436654   .0611907    -5.62   0.000
Non-gig worker vs Gig: side job  |  -.1544536   .0518381    -2.98   0.009
-------------------------------------------------------------------------
file Figures/crisisgov_nw.gph saved
file
    /Users/haselswerdtj/Library/CloudStorage/OneDrive-UniversityofMissouri/Miz
    > zou/Advising/Past students/Juhyun Bae/Gig Workers/Gig Workers JB &
    JH/Data/Figures/crisismerge_nw.png saved as PNG format

   Gig work |
main/side/n |
         on |       Summary of Likelihood of overcoming
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |           3           1         286         302
  Gig: side |           3           1         466         508
  Non-gig w |           3           1         675         679
------------+------------------------------------------------
      Total |           3           1       1,426       1,489

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      2.67914791      2   1.33957396      1.73     0.1781
 Within groups       1152.3541   1486   .775473826
------------------------------------------------------------------------
    Total           1155.03325   1488   .776232025

Bartlett's equal-variances test: chi2(2) =   2.2620    Prob>chi2 = 0.323

 Comparison of Likelihood of overcoming by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |          0
         |      0.343
         |
Non-gig  |          0         -0
         |      1.000      0.306

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |   .1011418   .0647698     1.56   0.356
Non-gig worker vs Gig: main job  |   .0165973   .0608298     0.27   1.000
Non-gig worker vs Gig: side job  |  -.0845445   .0519222    -1.63   0.311
-------------------------------------------------------------------------
file Figures/crisis_ww.gph saved

   Gig work |
main/side/n |
         on |  Summary of Helpfulness of government programs
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |           3           1         283         301
  Gig: side |           3           1         466         508
  Non-gig w |           3           1         675         679
------------+------------------------------------------------
      Total |           3           1       1,424       1,488

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      19.8753877      2   9.93769387     12.75     0.0000
 Within groups      1157.13608   1485   .779216218
------------------------------------------------------------------------
    Total           1177.01147   1487   .791534278

Bartlett's equal-variances test: chi2(2) =   0.8754    Prob>chi2 = 0.646

               Comparison of Helpfulness of government programs
                    by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |         -0
         |      0.026
         |
Non-gig  |         -0         -0
         |      0.000      0.028

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |  -.1687838   .0650739    -2.59   0.029
Non-gig worker vs Gig: main job  |  -.3035441   .0611338    -4.97   0.000
Non-gig worker vs Gig: side job  |  -.1347603   .0520201    -2.59   0.029
-------------------------------------------------------------------------
file Figures/crisisgov_ww.gph saved
file
    /Users/haselswerdtj/Library/CloudStorage/OneDrive-UniversityofMissouri/Miz
    > zou/Advising/Past students/Juhyun Bae/Gig Workers/Gig Workers JB &
    JH/Data/Figures/crisismerge_ww.png saved as PNG format

.                 
. //Figure 3 (formerly 4) - who/what should bear responsibility for benefits
. 
. foreach w in nw ww{
  2.         global graphlist
  3.         foreach i in 1 5 2 6 3 7{
  4.         local label: variable label mainprovider_`i'
  5.         local title=subinstr("`label'", "Main responsibility: ", "", .)
  6.         qui mlogit mainprovider_`i' i.gig_mainsidenon [pw=`w']
  7.         margins, over(gig_mainsidenon)
  8.         marginsplot, scheme(s1color) recast(scatter) plot1opts(msym(o)) plo
> t2opts(msym(t)) plot3opts(msym(s)) plot4opts(msym(d)) title("`title'") xtitle(
> "") xscale(r(.75 3.25)) legend(order(5 "Government" 6 "Employers" 7 "Charity" 
> 8 "Individual")  col(1) size(small)) ylabel(0(.2).8, grid) ytitle("")  xlabel(
> , labsize(medsmall)) saving(Figures/mainprovider_`i'_`w'.gph, replace)
  9.         global graphlist "$graphlist Figures/mainprovider_`i'_`w'.gph"
 10.         }
 11.         local noteoption = cond("`w'"=="ww", " note(Sampling weights used.)
> ", "")
 12. grc1leg $graphlist, col(2) pos(3) `noteoption'
 13. gr export Figures/mainprovider_`w'.png, as(png) replace
 14. }

Predictive margins                                       Number of obs = 1,488
Model VCE: Robust

Over: gig_mainsidenon

1._predict: Pr(mainprovider_1==Government), predict(pr outcome(1))
2._predict: Pr(mainprovider_1==Employers), predict(pr outcome(2))
3._predict: Pr(mainprovider_1==Non_profit_organization_or_chari), predict(pr
            outcome(3))
4._predict: Pr(mainprovider_1==Individual_themselves_or_their_f), predict(pr
            outcome(4))

-------------------------------------------------------------------------------
              |            Delta-method
              |     Margin   std. err.      z    P>|z|     [95% conf. interval]
--------------+----------------------------------------------------------------
     _predict#|
gig_mainsid~n |
           1 #|
Gig: main ..  |   .2880794   .0260684    11.05   0.000     .2369863    .3391726
           1 #|
Gig: side ..  |   .3333333   .0209428    15.92   0.000     .2922861    .3743806
           1 #|
Non-gig wo..  |   .3240059   .0179663    18.03   0.000     .2887926    .3592192
           2 #|
Gig: main ..  |   .4966886   .0287808    17.26   0.000     .4402793     .553098
           2 #|
Gig: side ..  |   .5384615   .0221474    24.31   0.000     .4950534    .5818697
           2 #|
Non-gig wo..  |   .5419735   .0191269    28.34   0.000     .5044854    .5794616
           3 #|
Gig: main ..  |   .0794702   .0155691     5.10   0.000     .0489553    .1099851
           3 #|
Gig: side ..  |    .061144   .0106443     5.74   0.000     .0402815    .0820065
           3 #|
Non-gig wo..  |   .0427099   .0077624     5.50   0.000     .0274958    .0579239
           4 #|
Gig: main ..  |   .1357617   .0197173     6.89   0.000     .0971165     .174407
           4 #|
Gig: side ..  |   .0670612   .0111123     6.03   0.000     .0452815    .0888409
           4 #|
Non-gig wo..  |   .0913108   .0110581     8.26   0.000     .0696373    .1129842
-------------------------------------------------------------------------------

Variables that uniquely identify margins: gig_mainsidenon
file Figures/mainprovider_1_nw.gph saved

Predictive margins                                       Number of obs = 1,483
Model VCE: Robust

Over: gig_mainsidenon

1._predict: Pr(mainprovider_5==Government), predict(pr outcome(1))
2._predict: Pr(mainprovider_5==Employers), predict(pr outcome(2))
3._predict: Pr(mainprovider_5==Non_profit_organization_or_chari), predict(pr
            outcome(3))
4._predict: Pr(mainprovider_5==Individual_themselves_or_their_f), predict(pr
            outcome(4))

-------------------------------------------------------------------------------
              |            Delta-method
              |     Margin   std. err.      z    P>|z|     [95% conf. interval]
--------------+----------------------------------------------------------------
     _predict#|
gig_mainsid~n |
           1 #|
Gig: main ..  |   .4481605   .0287696    15.58   0.000     .3917731    .5045479
           1 #|
Gig: side ..  |   .4782609   .0222142    21.53   0.000     .4347219    .5217999
           1 #|
Non-gig wo..  |   .4454277   .0190941    23.33   0.000      .408004    .4828515
           2 #|
Gig: main ..  |   .2541806   .0251883    10.09   0.000     .2048124    .3035488
           2 #|
Gig: side ..  |   .2411067   .0190224    12.67   0.000     .2038234      .27839
           2 #|
Non-gig wo..  |   .2138643   .0157525    13.58   0.000       .18299    .2447386
           3 #|
Gig: main ..  |   .1036789   .0176355     5.88   0.000      .069114    .1382439
           3 #|
Gig: side ..  |   .0731225   .0115773     6.32   0.000     .0504314    .0958137
           3 #|
Non-gig wo..  |   .0383481   .0073776     5.20   0.000     .0238883    .0528078
           4 #|
Gig: main ..  |   .1939799   .0228751     8.48   0.000     .1491456    .2388142
           4 #|
Gig: side ..  |   .2075099   .0180338    11.51   0.000     .1721643    .2428555
           4 #|
Non-gig wo..  |   .3023599   .0176445    17.14   0.000     .2677773    .3369425
-------------------------------------------------------------------------------

Variables that uniquely identify margins: gig_mainsidenon
file Figures/mainprovider_5_nw.gph saved

Predictive margins                                       Number of obs = 1,485
Model VCE: Robust

Over: gig_mainsidenon

1._predict: Pr(mainprovider_2==Government), predict(pr outcome(1))
2._predict: Pr(mainprovider_2==Employers), predict(pr outcome(2))
3._predict: Pr(mainprovider_2==Non_profit_organization_or_chari), predict(pr
            outcome(3))
4._predict: Pr(mainprovider_2==Individual_themselves_or_their_f), predict(pr
            outcome(4))

-------------------------------------------------------------------------------
              |            Delta-method
              |     Margin   std. err.      z    P>|z|     [95% conf. interval]
--------------+----------------------------------------------------------------
     _predict#|
gig_mainsid~n |
           1 #|
Gig: main ..  |   .5099338   .0287758    17.72   0.000     .4535343    .5663333
           1 #|
Gig: side ..  |   .5395257   .0221656    24.34   0.000     .4960819    .5829695
           1 #|
Non-gig wo..  |   .5731167   .0190164    30.14   0.000     .5358453    .6103881
           2 #|
Gig: main ..  |   .3046358   .0264935    11.50   0.000     .2527094    .3565621
           2 #|
Gig: side ..  |   .3399209   .0210648    16.14   0.000     .2986346    .3812073
           2 #|
Non-gig wo..  |   .3308715   .0180899    18.29   0.000     .2954159    .3663271
           3 #|
Gig: main ..  |   .0761589   .0152687     4.99   0.000     .0462329     .106085
           3 #|
Gig: side ..  |   .0731225   .0115773     6.32   0.000     .0504314    .0958136
           3 #|
Non-gig wo..  |   .0398818   .0075232     5.30   0.000     .0251367     .054627
           4 #|
Gig: main ..  |   .1092715   .0179585     6.08   0.000     .0740736    .1444694
           4 #|
Gig: side ..  |   .0474308   .0094526     5.02   0.000     .0289041    .0659575
           4 #|
Non-gig wo..  |     .05613   .0088492     6.34   0.000     .0387858    .0734742
-------------------------------------------------------------------------------

Variables that uniquely identify margins: gig_mainsidenon
file Figures/mainprovider_2_nw.gph saved

Predictive margins                                       Number of obs = 1,476
Model VCE: Robust

Over: gig_mainsidenon

1._predict: Pr(mainprovider_6==Government), predict(pr outcome(1))
2._predict: Pr(mainprovider_6==Employers), predict(pr outcome(2))
3._predict: Pr(mainprovider_6==Non_profit_organization_or_chari), predict(pr
            outcome(3))
4._predict: Pr(mainprovider_6==Individual_themselves_or_their_f), predict(pr
            outcome(4))

-------------------------------------------------------------------------------
              |            Delta-method
              |     Margin   std. err.      z    P>|z|     [95% conf. interval]
--------------+----------------------------------------------------------------
     _predict#|
gig_mainsid~n |
           1 #|
Gig: main ..  |   .5503356   .0288268    19.09   0.000      .493836    .6068351
           1 #|
Gig: side ..  |   .5544554   .0221249    25.06   0.000     .5110915    .5978194
           1 #|
Non-gig wo..  |   .5408618   .0192156    28.15   0.000     .5031999    .5785237
           2 #|
Gig: main ..  |    .204698   .0233809     8.75   0.000     .1588722    .2505238
           2 #|
Gig: side ..  |    .239604   .0190006    12.61   0.000     .2023634    .2768445
           2 #|
Non-gig wo..  |   .1723626    .014564    11.83   0.000     .1438176    .2009075
           3 #|
Gig: main ..  |   .1006711   .0174362     5.77   0.000     .0664969    .1348454
           3 #|
Gig: side ..  |   .0673267   .0111548     6.04   0.000     .0454638    .0891896
           3 #|
Non-gig wo..  |   .0490342   .0083267     5.89   0.000     .0327142    .0653542
           4 #|
Gig: main ..  |   .1442953   .0203623     7.09   0.000     .1043859    .1842047
           4 #|
Gig: side ..  |   .1386139   .0153817     9.01   0.000     .1084663    .1687614
           4 #|
Non-gig wo..  |   .2377415   .0164151    14.48   0.000     .2055685    .2699144
-------------------------------------------------------------------------------

Variables that uniquely identify margins: gig_mainsidenon
file Figures/mainprovider_6_nw.gph saved

Predictive margins                                       Number of obs = 1,487
Model VCE: Robust

Over: gig_mainsidenon

1._predict: Pr(mainprovider_3==Government), predict(pr outcome(1))
2._predict: Pr(mainprovider_3==Employers), predict(pr outcome(2))
3._predict: Pr(mainprovider_3==Non_profit_organization_or_chari), predict(pr
            outcome(3))
4._predict: Pr(mainprovider_3==Individual_themselves_or_their_f), predict(pr
            outcome(4))

-------------------------------------------------------------------------------
              |            Delta-method
              |     Margin   std. err.      z    P>|z|     [95% conf. interval]
--------------+----------------------------------------------------------------
     _predict#|
gig_mainsid~n |
           1 #|
Gig: main ..  |   .2657807   .0254705    10.43   0.000     .2158595     .315702
           1 #|
Gig: side ..  |   .2559055   .0193673    13.21   0.000     .2179464    .2938646
           1 #|
Non-gig wo..  |   .2817109   .0172816    16.30   0.000     .2478397    .3155821
           2 #|
Gig: main ..  |   .5581395   .0286337    19.49   0.000     .5020186    .6142605
           2 #|
Gig: side ..  |   .6299213   .0214291    29.40   0.000     .5879209    .6719216
           2 #|
Non-gig wo..  |   .6297935   .0185504    33.95   0.000     .5934355    .6661515
           3 #|
Gig: main ..  |   .0730897   .0150075     4.87   0.000     .0436754     .102504
           3 #|
Gig: side ..  |   .0570866   .0102972     5.54   0.000     .0369046    .0772687
           3 #|
Non-gig wo..  |   .0383481   .0073775     5.20   0.000     .0238884    .0528078
           4 #|
Gig: main ..  |     .10299    .017525     5.88   0.000     .0686416    .1373385
           4 #|
Gig: side ..  |   .0570866   .0102972     5.54   0.000     .0369046    .0772687
           4 #|
Non-gig wo..  |   .0501475   .0083846     5.98   0.000     .0337139    .0665811
-------------------------------------------------------------------------------

Variables that uniquely identify margins: gig_mainsidenon
file Figures/mainprovider_3_nw.gph saved

Predictive margins                                       Number of obs = 1,469
Model VCE: Robust

Over: gig_mainsidenon

1._predict: Pr(mainprovider_7==Government), predict(pr outcome(1))
2._predict: Pr(mainprovider_7==Employers), predict(pr outcome(2))
3._predict: Pr(mainprovider_7==Non_profit_organization_or_chari), predict(pr
            outcome(3))
4._predict: Pr(mainprovider_7==Individual_themselves_or_their_f), predict(pr
            outcome(4))

-------------------------------------------------------------------------------
              |            Delta-method
              |     Margin   std. err.      z    P>|z|     [95% conf. interval]
--------------+----------------------------------------------------------------
     _predict#|
gig_mainsid~n |
           1 #|
Gig: main ..  |   .4087838   .0285839    14.30   0.000     .3527603    .4648073
           1 #|
Gig: side ..  |   .4493042   .0221866    20.25   0.000     .4058193     .492789
           1 #|
Non-gig wo..  |   .4208955   .0190799    22.06   0.000     .3834996    .4582914
           2 #|
Gig: main ..  |   .2871622   .0263064    10.92   0.000     .2356026    .3387217
           2 #|
Gig: side ..  |   .3419483    .021158    16.16   0.000     .3004794    .3834172
           2 #|
Non-gig wo..  |   .2716418   .0171902    15.80   0.000     .2379496     .305334
           3 #|
Gig: main ..  |   .1385135    .020085     6.90   0.000     .0991476    .1778794
           3 #|
Gig: side ..  |   .0616302   .0107262     5.75   0.000     .0406072    .0826533
           3 #|
Non-gig wo..  |   .0492537    .008363     5.89   0.000     .0328625    .0656449
           4 #|
Gig: main ..  |   .1655405   .0216101     7.66   0.000     .1231855    .2078956
           4 #|
Gig: side ..  |   .1471173   .0157994     9.31   0.000     .1161511    .1780835
           4 #|
Non-gig wo..  |    .258209   .0169136    15.27   0.000     .2250588    .2913591
-------------------------------------------------------------------------------

Variables that uniquely identify margins: gig_mainsidenon
file Figures/mainprovider_7_nw.gph saved
file
    /Users/haselswerdtj/Library/CloudStorage/OneDrive-UniversityofMissouri/Miz
    > zou/Advising/Past students/Juhyun Bae/Gig Workers/Gig Workers JB &
    JH/Data/Figures/mainprovider_nw.png saved as PNG format

Predictive margins                                       Number of obs = 1,488
Model VCE: Robust

Over: gig_mainsidenon

1._predict: Pr(mainprovider_1==Government), predict(pr outcome(1))
2._predict: Pr(mainprovider_1==Employers), predict(pr outcome(2))
3._predict: Pr(mainprovider_1==Non_profit_organization_or_chari), predict(pr
            outcome(3))
4._predict: Pr(mainprovider_1==Individual_themselves_or_their_f), predict(pr
            outcome(4))

-------------------------------------------------------------------------------
              |            Delta-method
              |     Margin   std. err.      z    P>|z|     [95% conf. interval]
--------------+----------------------------------------------------------------
     _predict#|
gig_mainsid~n |
           1 #|
Gig: main ..  |   .2805506   .0325493     8.62   0.000     .2167552     .344346
           1 #|
Gig: side ..  |   .3421126    .026875    12.73   0.000     .2894387    .3947866
           1 #|
Non-gig wo..  |   .3197524   .0211596    15.11   0.000     .2782804    .3612244
           2 #|
Gig: main ..  |   .4486677   .0365944    12.26   0.000     .3769439    .5203914
           2 #|
Gig: side ..  |   .5226504   .0282179    18.52   0.000     .4673442    .5779565
           2 #|
Non-gig wo..  |   .5438349   .0225242    24.14   0.000     .4996884    .5879815
           3 #|
Gig: main ..  |   .1390805   .0302349     4.60   0.000     .0798213    .1983398
           3 #|
Gig: side ..  |   .0816452   .0174111     4.69   0.000     .0475201    .1157703
           3 #|
Non-gig wo..  |   .0368797   .0076737     4.81   0.000     .0218395    .0519198
           4 #|
Gig: main ..  |   .1317012   .0239004     5.51   0.000     .0848572    .1785452
           4 #|
Gig: side ..  |   .0535917   .0120491     4.45   0.000     .0299759    .0772076
           4 #|
Non-gig wo..  |    .099533    .013978     7.12   0.000     .0721367    .1269293
-------------------------------------------------------------------------------

Variables that uniquely identify margins: gig_mainsidenon
file Figures/mainprovider_1_ww.gph saved

Predictive margins                                       Number of obs = 1,483
Model VCE: Robust

Over: gig_mainsidenon

1._predict: Pr(mainprovider_5==Government), predict(pr outcome(1))
2._predict: Pr(mainprovider_5==Employers), predict(pr outcome(2))
3._predict: Pr(mainprovider_5==Non_profit_organization_or_chari), predict(pr
            outcome(3))
4._predict: Pr(mainprovider_5==Individual_themselves_or_their_f), predict(pr
            outcome(4))

-------------------------------------------------------------------------------
              |            Delta-method
              |     Margin   std. err.      z    P>|z|     [95% conf. interval]
--------------+----------------------------------------------------------------
     _predict#|
gig_mainsid~n |
           1 #|
Gig: main ..  |   .3858074   .0352366    10.95   0.000     .3167448    .4548699
           1 #|
Gig: side ..  |   .4653932   .0281566    16.53   0.000     .4102073    .5205792
           1 #|
Non-gig wo..  |   .4285572   .0222771    19.24   0.000     .3848948    .4722195
           2 #|
Gig: main ..  |   .2882331   .0349228     8.25   0.000     .2197856    .3566806
           2 #|
Gig: side ..  |   .2444723   .0238129    10.27   0.000     .1977998    .2911448
           2 #|
Non-gig wo..  |    .228165   .0193703    11.78   0.000     .1901999    .2661301
           3 #|
Gig: main ..  |   .1411393   .0287404     4.91   0.000     .0848092    .1974694
           3 #|
Gig: side ..  |   .0696341   .0140179     4.97   0.000     .0421596    .0971086
           3 #|
Non-gig wo..  |   .0363595   .0083176     4.37   0.000     .0200573    .0526616
           4 #|
Gig: main ..  |   .1848202   .0280963     6.58   0.000     .1297524     .239888
           4 #|
Gig: side ..  |   .2205003   .0239393     9.21   0.000     .1735801    .2674205
           4 #|
Non-gig wo..  |   .3069183   .0209128    14.68   0.000     .2659301    .3479066
-------------------------------------------------------------------------------

Variables that uniquely identify margins: gig_mainsidenon
file Figures/mainprovider_5_ww.gph saved

Predictive margins                                       Number of obs = 1,485
Model VCE: Robust

Over: gig_mainsidenon

1._predict: Pr(mainprovider_2==Government), predict(pr outcome(1))
2._predict: Pr(mainprovider_2==Employers), predict(pr outcome(2))
3._predict: Pr(mainprovider_2==Non_profit_organization_or_chari), predict(pr
            outcome(3))
4._predict: Pr(mainprovider_2==Individual_themselves_or_their_f), predict(pr
            outcome(4))

-------------------------------------------------------------------------------
              |            Delta-method
              |     Margin   std. err.      z    P>|z|     [95% conf. interval]
--------------+----------------------------------------------------------------
     _predict#|
gig_mainsid~n |
           1 #|
Gig: main ..  |   .4769766   .0369025    12.93   0.000      .404649    .5493041
           1 #|
Gig: side ..  |   .5345662   .0282194    18.94   0.000     .4792571    .5898752
           1 #|
Non-gig wo..  |   .5858261   .0220824    26.53   0.000     .5425454    .6291068
           2 #|
Gig: main ..  |   .2776976   .0322559     8.61   0.000     .2144772    .3409181
           2 #|
Gig: side ..  |   .3440221   .0270128    12.74   0.000     .2910779    .3969662
           2 #|
Non-gig wo..  |   .3182129   .0206065    15.44   0.000     .2778249    .3586009
           3 #|
Gig: main ..  |   .1223111   .0281247     4.35   0.000     .0671877    .1774346
           3 #|
Gig: side ..  |   .0726659   .0151866     4.78   0.000     .0429008     .102431
           3 #|
Non-gig wo..  |   .0374708    .008541     4.39   0.000     .0207308    .0542108
           4 #|
Gig: main ..  |   .1230146    .024467     5.03   0.000     .0750602     .170969
           4 #|
Gig: side ..  |   .0487459   .0122416     3.98   0.000     .0247528    .0727389
           4 #|
Non-gig wo..  |   .0584902    .010683     5.48   0.000      .037552    .0794284
-------------------------------------------------------------------------------

Variables that uniquely identify margins: gig_mainsidenon
file Figures/mainprovider_2_ww.gph saved

Predictive margins                                       Number of obs = 1,476
Model VCE: Robust

Over: gig_mainsidenon

1._predict: Pr(mainprovider_6==Government), predict(pr outcome(1))
2._predict: Pr(mainprovider_6==Employers), predict(pr outcome(2))
3._predict: Pr(mainprovider_6==Non_profit_organization_or_chari), predict(pr
            outcome(3))
4._predict: Pr(mainprovider_6==Individual_themselves_or_their_f), predict(pr
            outcome(4))

-------------------------------------------------------------------------------
              |            Delta-method
              |     Margin   std. err.      z    P>|z|     [95% conf. interval]
--------------+----------------------------------------------------------------
     _predict#|
gig_mainsid~n |
           1 #|
Gig: main ..  |   .4844285   .0371431    13.04   0.000     .4116293    .5572277
           1 #|
Gig: side ..  |   .5408711   .0282136    19.17   0.000     .4855734    .5961688
           1 #|
Non-gig wo..  |   .5350096   .0226018    23.67   0.000     .4907109    .5793082
           2 #|
Gig: main ..  |     .21773   .0317542     6.86   0.000     .1554928    .2799672
           2 #|
Gig: side ..  |   .2321066   .0233986     9.92   0.000     .1862463     .277967
           2 #|
Non-gig wo..  |   .1741354   .0168007    10.36   0.000     .1412065    .2070642
           3 #|
Gig: main ..  |   .1509817   .0308201     4.90   0.000     .0905755     .211388
           3 #|
Gig: side ..  |   .0831755   .0162076     5.13   0.000     .0514092    .1149418
           3 #|
Non-gig wo..  |    .048894   .0096876     5.05   0.000     .0299065    .0678814
           4 #|
Gig: main ..  |   .1468598   .0260141     5.65   0.000      .095873    .1978466
           4 #|
Gig: side ..  |   .1438468   .0206849     6.95   0.000     .1033051    .1843885
           4 #|
Non-gig wo..  |   .2419611   .0194502    12.44   0.000     .2038394    .2800828
-------------------------------------------------------------------------------

Variables that uniquely identify margins: gig_mainsidenon
file Figures/mainprovider_6_ww.gph saved

Predictive margins                                       Number of obs = 1,487
Model VCE: Robust

Over: gig_mainsidenon

1._predict: Pr(mainprovider_3==Government), predict(pr outcome(1))
2._predict: Pr(mainprovider_3==Employers), predict(pr outcome(2))
3._predict: Pr(mainprovider_3==Non_profit_organization_or_chari), predict(pr
            outcome(3))
4._predict: Pr(mainprovider_3==Individual_themselves_or_their_f), predict(pr
            outcome(4))

-------------------------------------------------------------------------------
              |            Delta-method
              |     Margin   std. err.      z    P>|z|     [95% conf. interval]
--------------+----------------------------------------------------------------
     _predict#|
gig_mainsid~n |
           1 #|
Gig: main ..  |   .2444225   .0315807     7.74   0.000     .1825256    .3063195
           1 #|
Gig: side ..  |   .2757144   .0255941    10.77   0.000     .2255509    .3258779
           1 #|
Non-gig wo..  |   .2953003   .0211193    13.98   0.000     .2539073    .3366933
           2 #|
Gig: main ..  |   .5263759    .037175    14.16   0.000     .4535142    .5992375
           2 #|
Gig: side ..  |   .5958954   .0278755    21.38   0.000     .5412604    .6505303
           2 #|
Non-gig wo..  |   .6223557   .0220967    28.17   0.000     .5790469    .6656644
           3 #|
Gig: main ..  |   .1306716   .0288854     4.52   0.000     .0740572     .187286
           3 #|
Gig: side ..  |   .0588222   .0131511     4.47   0.000     .0330465    .0845978
           3 #|
Non-gig wo..  |   .0311817   .0064435     4.84   0.000     .0185527    .0438108
           4 #|
Gig: main ..  |     .09853   .0209081     4.71   0.000     .0575508    .1395092
           4 #|
Gig: side ..  |   .0695681   .0150636     4.62   0.000     .0400439    .0990922
           4 #|
Non-gig wo..  |   .0511623   .0101214     5.05   0.000     .0313247    .0709999
-------------------------------------------------------------------------------

Variables that uniquely identify margins: gig_mainsidenon
file Figures/mainprovider_3_ww.gph saved

Predictive margins                                       Number of obs = 1,469
Model VCE: Robust

Over: gig_mainsidenon

1._predict: Pr(mainprovider_7==Government), predict(pr outcome(1))
2._predict: Pr(mainprovider_7==Employers), predict(pr outcome(2))
3._predict: Pr(mainprovider_7==Non_profit_organization_or_chari), predict(pr
            outcome(3))
4._predict: Pr(mainprovider_7==Individual_themselves_or_their_f), predict(pr
            outcome(4))

-------------------------------------------------------------------------------
              |            Delta-method
              |     Margin   std. err.      z    P>|z|     [95% conf. interval]
--------------+----------------------------------------------------------------
     _predict#|
gig_mainsid~n |
           1 #|
Gig: main ..  |   .3807724   .0357111    10.66   0.000     .3107799    .4507649
           1 #|
Gig: side ..  |   .4493541   .0281826    15.94   0.000     .3941173    .5045909
           1 #|
Non-gig wo..  |   .4248341   .0226277    18.77   0.000     .3804846    .4691836
           2 #|
Gig: main ..  |   .2389208   .0304917     7.84   0.000     .1791583    .2986834
           2 #|
Gig: side ..  |   .3294337   .0262251    12.56   0.000     .2780335    .3808338
           2 #|
Non-gig wo..  |   .2749897   .0202213    13.60   0.000     .2353567    .3146228
           3 #|
Gig: main ..  |   .1955052   .0325825     6.00   0.000     .1316447    .2593657
           3 #|
Gig: side ..  |   .0747222   .0157491     4.74   0.000     .0438544    .1055899
           3 #|
Non-gig wo..  |   .0462846   .0091283     5.07   0.000     .0283935    .0641756
           4 #|
Gig: main ..  |   .1848016   .0297203     6.22   0.000     .1265509    .2430523
           4 #|
Gig: side ..  |   .1464901   .0207062     7.07   0.000     .1059068    .1870734
           4 #|
Non-gig wo..  |   .2538916   .0194975    13.02   0.000     .2156772     .292106
-------------------------------------------------------------------------------

Variables that uniquely identify margins: gig_mainsidenon
file Figures/mainprovider_7_ww.gph saved
file
    /Users/haselswerdtj/Library/CloudStorage/OneDrive-UniversityofMissouri/Miz
    > zou/Advising/Past students/Juhyun Bae/Gig Workers/Gig Workers JB &
    JH/Data/Figures/mainprovider_ww.png saved as PNG format

. 
. 
. //Figure 4 (formerly 5) - social welfare for nonstandard workers
. foreach w in nw ww{
  2.         foreach i in 1 2{
  3.                 local label: variable label UIhealth_`i'
  4.                 local Title = subinstr("`label'", "Expansion ", "", .)
  5.                 local Title = subinstr("`Title'", "to cover", "for", .)
  6.                 onewaygraph UIhealth_`i' gig_mainsidenon [aw=`w'], bo graph
> _option(scheme(s1color) ylabel(1(0.5)5, grid) xtitle(`Title' , size(m))) nonot
> e
  7.                 graph save "Figures/UIhealth_`i'_`w'.gph", replace
  8.         }
  9.         local note = cond("`w'"=="ww", " Sampling weights used.", "")
 10.         grc1leg "Figures/UIhealth_1_`w'.gph" "Figures/UIhealth_2_`w'.gph", 
> scheme(s1color) note("Note: *p < 0.1, **p<0.05, ***p<0.01 `note'") 
 11.                         gr export "Figures/UIHImerge_`w'.png", as(png) repl
> ace // JB: 04-03: add the combined one
 12. }

   Gig work |
main/side/n |  Summary of Expansion UI to cover non-standard
         on |                     workers
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |           4           1         302         302
  Gig: side |           4           1         507         507
  Non-gig w |           3           1         678         678
------------+------------------------------------------------
      Total |           3           1       1,487       1,487

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      46.6546557      2   23.3273278     15.93     0.0000
 Within groups      2172.88939   1484   1.46421118
------------------------------------------------------------------------
    Total           2219.54405   1486   1.49363664

Bartlett's equal-variances test: chi2(2) =   3.4288    Prob>chi2 = 0.180

           Comparison of Expansion UI to cover non-standard workers
                    by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |         -0
         |      0.150
         |
Non-gig  |         -0         -0
         |      0.000      0.000

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |  -.1724075   .0879566    -1.96   0.150
Non-gig worker vs Gig: main job  |  -.4415597   .0837137    -5.27   0.000
Non-gig worker vs Gig: side job  |  -.2691522   .0710464    -3.79   0.000
-------------------------------------------------------------------------
(note:  named style m not found in class gsize, default attributes used)
file Figures/UIhealth_1_nw.gph saved

   Gig work |
main/side/n |  Summary of Expansion HI to cover non-standard
         on |                     workers
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |           4           1         302         302
  Gig: side |           4           1         508         508
  Non-gig w |           3           1         679         679
------------+------------------------------------------------
      Total |           4           1       1,489       1,489

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups       41.253021      2   20.6265105     14.55     0.0000
 Within groups      2107.25067   1486   1.41806909
------------------------------------------------------------------------
    Total           2148.50369   1488   1.44388689

Bartlett's equal-variances test: chi2(2) =   5.3149    Prob>chi2 = 0.070

           Comparison of Expansion HI to cover non-standard workers
                    by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |         -0
         |      1.000
         |
Non-gig  |         -0         -0
         |      0.000      0.000

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |  -.0785185   .0865278    -0.91   1.000
Non-gig worker vs Gig: main job  |  -.3786734   .0823654    -4.60   0.000
Non-gig worker vs Gig: side job  |  -.3001548   .0698566    -4.30   0.000
-------------------------------------------------------------------------
(note:  named style m not found in class gsize, default attributes used)
file Figures/UIhealth_2_nw.gph saved
(note:  named style m not found in class gsize, default attributes used)
(note:  named style m not found in class gsize, default attributes used)
file
    /Users/haselswerdtj/Library/CloudStorage/OneDrive-UniversityofMissouri/Miz
    > zou/Advising/Past students/Juhyun Bae/Gig Workers/Gig Workers JB &
    JH/Data/Figures/UIHImerge_nw.png saved as PNG format

   Gig work |
main/side/n |  Summary of Expansion UI to cover non-standard
         on |                     workers
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |           4           1         286         302
  Gig: side |           4           1         464         507
  Non-gig w |           3           1         675         678
------------+------------------------------------------------
      Total |           3           1       1,425       1,487

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      27.6808248      2   13.8404124      9.70     0.0001
 Within groups      2118.15139   1484   1.42732574
------------------------------------------------------------------------
    Total           2145.83222   1486   1.44403245

Bartlett's equal-variances test: chi2(2) =   8.6175    Prob>chi2 = 0.013

           Comparison of Expansion UI to cover non-standard workers
                    by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |         -0
         |      0.406
         |
Non-gig  |         -0         -0
         |      0.000      0.009

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |  -.1297811   .0879257    -1.48   0.420
Non-gig worker vs Gig: main job  |  -.3377951   .0825412    -4.09   0.000
Non-gig worker vs Gig: side job  |   -.208014   .0705136    -2.95   0.010
-------------------------------------------------------------------------
(note:  named style m not found in class gsize, default attributes used)
file Figures/UIhealth_1_ww.gph saved

   Gig work |
main/side/n |  Summary of Expansion HI to cover non-standard
         on |                     workers
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |           4           1         286         302
  Gig: side |           4           1         466         508
  Non-gig w |           3           1         675         679
------------+------------------------------------------------
      Total |           4           1       1,427       1,489

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      30.0268736      2   15.0134368     10.62     0.0000
 Within groups      2100.98222   1486   1.41385075
------------------------------------------------------------------------
    Total           2131.00909   1488   1.43212977

Bartlett's equal-variances test: chi2(2) =  13.7967    Prob>chi2 = 0.001

           Comparison of Expansion HI to cover non-standard workers
                    by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |         -0
         |      1.000
         |
Non-gig  |         -0         -0
         |      0.001      0.000

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |  -.0045223   .0874649    -0.05   1.000
Non-gig worker vs Gig: main job  |   -.287202   .0821393    -3.50   0.001
Non-gig worker vs Gig: side job  |  -.2826797   .0701095    -4.03   0.000
-------------------------------------------------------------------------
(note:  named style m not found in class gsize, default attributes used)
file Figures/UIhealth_2_ww.gph saved
(note:  named style m not found in class gsize, default attributes used)
(note:  named style m not found in class gsize, default attributes used)
file
    /Users/haselswerdtj/Library/CloudStorage/OneDrive-UniversityofMissouri/Miz
    > zou/Advising/Past students/Juhyun Bae/Gig Workers/Gig Workers JB &
    JH/Data/Figures/UIHImerge_ww.png saved as PNG format

. 
. //Figure 5 (formerly 6) - Biden rule
. 
. foreach w in nw ww{
  2.         onewaygraph Biden_rule_support gig_mainsidenon [aw=`w'], bo graph_o
> ption(scheme(s1color) ylabel(1(1)5, grid) xtitle(Biden rule support, size(m)))
>  nonote
  3. graph save "Figures/Biden_`w'.gph", replace
  4.         onewaygraph Biden_rule_knowledge gig_mainsidenon [aw=`w'], bo graph
> _option(scheme(s1color) ylabel(1(1)3, grid) xtitle(Biden rule knowledge, size(
> m))) nonote 
  5. graph save "Figures/Bidenknow_`w'.gph", replace
  6.         local note = cond("`w'"=="ww", " Sampling weights used.", "")
  7.         grc1leg "Figures/Bidenknow_`w'.gph" "Figures/Biden_`w'.gph" , legen
> dfrom("Figures/Biden_`w'.gph") cols(3) imargin(2 2 2 2) scheme(s1color) note("
> Note: *p < 0.1, **p<0.05, ***p<0.01 `note'") 
  8. graph export Figures/Biden_rule_combined_`w'.png, replace 
  9. }

   Gig work |
main/side/n |
         on |          Summary of Biden rule support
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |           4           1         302         302
  Gig: side |           4           1         508         508
  Non-gig w |           3           1         679         679
------------+------------------------------------------------
      Total |           4           1       1,489       1,489

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups       12.279652      2   6.13982601      5.63     0.0037
 Within groups      1620.11927   1486   1.09025523
------------------------------------------------------------------------
    Total           1632.39893   1488   1.09704229

Bartlett's equal-variances test: chi2(2) =   5.6715    Prob>chi2 = 0.059

    Comparison of Biden rule support by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |         -0
         |      0.626
         |
Non-gig  |         -0         -0
         |      0.005      0.088

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |  -.0954138   .0758702    -1.26   0.626
Non-gig worker vs Gig: main job  |  -.2288865   .0722205    -3.17   0.005
Non-gig worker vs Gig: side job  |  -.1334727   .0612523    -2.18   0.088
-------------------------------------------------------------------------
(note:  named style m not found in class gsize, default attributes used)
file Figures/Biden_nw.gph saved

   Gig work |
main/side/n |
         on |         Summary of Biden rule knowledge
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |           2           1         302         302
  Gig: side |           2           1         506         506
  Non-gig w |           2           1         679         679
------------+------------------------------------------------
      Total |           2           1       1,487       1,487

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups       33.139881      2   16.5699405     40.20     0.0000
 Within groups      611.751847   1484   .412231703
------------------------------------------------------------------------
    Total           644.891728   1486   .433978283

Bartlett's equal-variances test: chi2(2) =  17.9914    Prob>chi2 = 0.000

   Comparison of Biden rule knowledge by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |         -0
         |      0.022
         |
Non-gig  |         -0         -0
         |      0.000      0.000

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |  -.1255791   .0466872    -2.69   0.022
Non-gig worker vs Gig: main job  |  -.3645408   .0444086    -8.21   0.000
Non-gig worker vs Gig: side job  |  -.2389616   .0377068    -6.34   0.000
-------------------------------------------------------------------------
(note:  named style m not found in class gsize, default attributes used)
file Figures/Bidenknow_nw.gph saved
(note:  named style m not found in class gsize, default attributes used)
(note:  named style m not found in class gsize, default attributes used)
file
    /Users/haselswerdtj/Library/CloudStorage/OneDrive-UniversityofMissouri/Miz
    > zou/Advising/Past students/Juhyun Bae/Gig Workers/Gig Workers JB &
    JH/Data/Figures/Biden_rule_combined_nw.png saved as PNG format

   Gig work |
main/side/n |
         on |          Summary of Biden rule support
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |           4           1         286         302
  Gig: side |           4           1         466         508
  Non-gig w |           3           1         675         679
------------+------------------------------------------------
      Total |           4           1       1,426       1,489

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      10.0684159      2   5.03420796      4.75     0.0088
 Within groups      1574.78375   1486    1.0597468
------------------------------------------------------------------------
    Total           1584.85216   1488   1.06508882

Bartlett's equal-variances test: chi2(2) =   5.1713    Prob>chi2 = 0.075

    Comparison of Biden rule support by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |         -0
         |      1.000
         |
Non-gig  |         -0         -0
         |      0.024      0.049

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |  -.0440815   .0757206    -0.58   1.000
Non-gig worker vs Gig: main job  |  -.1890496    .071112    -2.66   0.024
Non-gig worker vs Gig: side job  |  -.1449682   .0606979    -2.39   0.051
-------------------------------------------------------------------------
(note:  named style m not found in class gsize, default attributes used)
file Figures/Biden_ww.gph saved

   Gig work |
main/side/n |
         on |         Summary of Biden rule knowledge
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |           2           1         286         302
  Gig: side |           2           1         463         506
  Non-gig w |           2           1         675         679
------------+------------------------------------------------
      Total |           2           1       1,424       1,487

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      32.1627255      2   16.0813627     39.51     0.0000
 Within groups      604.068014   1484   .407053918
------------------------------------------------------------------------
    Total           636.230739   1486   .428149892

Bartlett's equal-variances test: chi2(2) =  13.5385    Prob>chi2 = 0.001

   Comparison of Biden rule knowledge by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |         -0
         |      0.041
         |
Non-gig  |         -0         -0
         |      0.000      0.000

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |  -.1143821   .0469656    -2.44   0.045
Non-gig worker vs Gig: main job  |  -.3539945   .0440613    -8.03   0.000
Non-gig worker vs Gig: side job  |  -.2396124   .0376714    -6.36   0.000
-------------------------------------------------------------------------
(note:  named style m not found in class gsize, default attributes used)
file Figures/Bidenknow_ww.gph saved
(note:  named style m not found in class gsize, default attributes used)
(note:  named style m not found in class gsize, default attributes used)
file
    /Users/haselswerdtj/Library/CloudStorage/OneDrive-UniversityofMissouri/Miz
    > zou/Advising/Past students/Juhyun Bae/Gig Workers/Gig Workers JB &
    JH/Data/Figures/Biden_rule_combined_ww.png saved as PNG format

.  
. 
.  
. //Figure 6 (formerly 7) - Participation
. 
.  foreach w in nw ww{
  2.         onewaygraph turnout_total gig_mainsidenon [aw=`w'], bo graph_option
> (scheme(s1color) ylabel(1(1)5, grid) xtitle(Turnout Total, size(m))) nonote
  3. graph save "Figures/turnout_`w'.gph", replace
  4.         onewaygraph otherpart_total gig_mainsidenon [aw=`w'], bo graph_opti
> on(scheme(s1color) ylabel(0(1)5, grid) xtitle(Other Political Participation To
> tal, size(m))) nonote 
  5. graph save "Figures/otherpart_`w'.gph", replace
  6.         local note = cond("`w'"=="ww", " Sampling weights used.", "")
  7.         grc1leg "Figures/turnout_`w'.gph" "Figures/otherpart_`w'.gph", lege
> ndfrom("Figures/turnout_`w'.gph") cols(3) imargin(2 2 2 2) scheme(s1color) not
> e("Note: *p < 0.1, **p<0.05, ***p<0.01 `note'") 
  8. graph export Figures/participation_`w'.png, replace 
  9. }

   Gig work |
main/side/n |
         on |            Summary of Total turnout
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |   2.3741722    1.848694         302         302
  Gig: side |   2.7992126   1.8776794         508         508
  Non-gig w |   2.7955882   1.9735313         680         680
------------+------------------------------------------------
      Total |   2.7114094   1.9225965       1,490       1,490

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      43.0810475      2   21.5405237      5.87     0.0029
 Within groups      5460.82499   1487   3.67237726
------------------------------------------------------------------------
    Total           5503.90604   1489   3.69637746

Bartlett's equal-variances test: chi2(2) =   2.3701    Prob>chi2 = 0.306

      Comparison of Total turnout by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |     .42504
         |      0.007
         |
Non-gig  |    .421416   -.003624
         |      0.005      1.000

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |   .4250404   .1392454     3.05   0.007
Non-gig worker vs Gig: main job  |    .421416    .132517     3.18   0.005
Non-gig worker vs Gig: side job  |  -.0036244   .1123817    -0.03   1.000
-------------------------------------------------------------------------
(note:  named style m not found in class gsize, default attributes used)
file Figures/turnout_nw.gph saved

   Gig work |
main/side/n |
         on |           Summary of otherpart_total
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |   .86092715   1.0151002         302         302
  Gig: side |    .8011811   1.0175184         508         508
  Non-gig w |   .53970588   .77414777         680         680
------------+------------------------------------------------
      Total |   .69395973   .92442625       1,490       1,490

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      30.4394647      2   15.2197323     18.22     0.0000
 Within groups      1242.00617   1487   .835242887
------------------------------------------------------------------------
    Total           1272.44564   1489   .854563894

Bartlett's equal-variances test: chi2(2) =  53.2428    Prob>chi2 = 0.000

       Comparison of otherpart_~l by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |   -.059746
         |      1.000
         |
Non-gig  |   -.321221   -.261475
         |      0.000      0.000

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |   -.059746    .066407    -0.90   1.000
Non-gig worker vs Gig: main job  |  -.3212213   .0631981    -5.08   0.000
Non-gig worker vs Gig: side job  |  -.2614752   .0535955    -4.88   0.000
-------------------------------------------------------------------------
(note:  named style m not found in class gsize, default attributes used)
file Figures/otherpart_nw.gph saved
(note:  named style m not found in class gsize, default attributes used)
(note:  named style m not found in class gsize, default attributes used)
file
    /Users/haselswerdtj/Library/CloudStorage/OneDrive-UniversityofMissouri/Miz
    > zou/Advising/Past students/Juhyun Bae/Gig Workers/Gig Workers JB &
    JH/Data/Figures/participation_nw.png saved as PNG format

   Gig work |
main/side/n |
         on |            Summary of Total turnout
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |   2.2429169   1.7788581         286         302
  Gig: side |   2.6848142    1.868525         466         508
  Non-gig w |   2.9065563   1.9568642         676         680
------------+------------------------------------------------
      Total |   2.7013546   1.9087917       1,427       1,490

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      92.5368443      2   46.2684221     12.90     0.0000
 Within groups      5332.61369   1487   3.58615581
------------------------------------------------------------------------
    Total           5425.15053   1489   3.64348592

Bartlett's equal-variances test: chi2(2) =   7.6512    Prob>chi2 = 0.022

      Comparison of Total turnout by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |    .441897
         |      0.004
         |
Non-gig  |    .663639    .221742
         |      0.000      0.138

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |   .4418973   .1392822     3.17   0.005
Non-gig worker vs Gig: main job  |   .6636394   .1307835     5.07   0.000
Non-gig worker vs Gig: side job  |   .2217421   .1116239     1.99   0.141
-------------------------------------------------------------------------
(note:  named style m not found in class gsize, default attributes used)
file Figures/turnout_ww.gph saved

   Gig work |
main/side/n |
         on |           Summary of otherpart_total
categorical |        Mean   Std. dev.       Freq.         Obs
------------+------------------------------------------------
  Gig: main |   .87600099   1.0510691         286         302
  Gig: side |   .79951383   .99141018         466         508
  Non-gig w |   .52893628   .74682002         676         680
------------+------------------------------------------------
      Total |   .68669109   .90987269       1,427       1,490

                        Analysis of variance
    Source              SS         df      MS            F     Prob > F
------------------------------------------------------------------------
Between groups      34.4381825      2   17.2190912     21.37     0.0000
 Within groups      1198.25774   1487   .805822287
------------------------------------------------------------------------
    Total           1232.69592   1489   .827868316

Bartlett's equal-variances test: chi2(2) =  55.0787    Prob>chi2 = 0.000

       Comparison of otherpart_~l by Gig work main/side/non categorical
                                (Bonferroni)
Row Mean-|
Col Mean |   Gig: mai   Gig: sid
---------+----------------------
Gig: sid |   -.076487
         |      0.723
         |
Non-gig  |   -.347065   -.270578
         |      0.000      0.000

Pairwise comparisons of marginal linear predictions

Margins: asbalanced

------------------------------
                |    Number of
                |  comparisons
----------------+-------------
gig_mainsidenon |            3
------------------------------

-------------------------------------------------------------------------
                                 |                            Bonferroni
                                 |   Contrast   Std. err.      t    P>|t|
---------------------------------+---------------------------------------
                 gig_mainsidenon |
 Gig: side job vs Gig: main job  |  -.0764872   .0660238    -1.16   0.741
Non-gig worker vs Gig: main job  |  -.3470647   .0619952    -5.60   0.000
Non-gig worker vs Gig: side job  |  -.2705776    .052913    -5.11   0.000
-------------------------------------------------------------------------
(note:  named style m not found in class gsize, default attributes used)
file Figures/otherpart_ww.gph saved
(note:  named style m not found in class gsize, default attributes used)
(note:  named style m not found in class gsize, default attributes used)
file
    /Users/haselswerdtj/Library/CloudStorage/OneDrive-UniversityofMissouri/Miz
    > zou/Advising/Past students/Juhyun Bae/Gig Workers/Gig Workers JB &
    JH/Data/Figures/participation_ww.png saved as PNG format

.  
. log close
      name:  <unnamed>
       log:  /Users/haselswerdtj/Library/CloudStorage/OneDrive-UniversityofMisso
> uri/Mizzou/Advising/Past students/Juhyun Bae/Gig Workers/Gig Workers JB & JH/D
> ata/gig_analysis.log
  log type:  text
 closed on:  25 Jun 2025, 10:24:18
--------------------------------------------------------------------------------
